In this paper we describe the properties of independent components of optical ow of moving objects. Video sequences of objects seen by an observer moving at various angles, direct...
Marwan A. Jabri, Ki-Young Park, Soo-Young Lee, Ter...
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
In independent component analysis problems, when we use a one-unit objective function to iteratively estimate several independent components, the uncorrelatedness between the indep...
Abstract. In this paper we examine how the activation of one independent component analysis (ICA) feature changes first and second order statistics of other independent components...
Abstract. The authors propose a new solution to the blind robust watermarking of digital images. In this approach we embed the watermark into the independent components of the imag...
HiPerSAT, a C++ library and tools, processes EEG data sets with ICA (Independent Component Analysis) methods. HiPerSAT uses BLAS, LAPACK, MPI and OpenMP to achieve a high performa...
D. B. Keith, C. C. Hoge, Robert M. Frank, Allen D....
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
FastICA is arguably one of the most widespread methods for independent component analysis. We focus on its deflation-based implementation, where the independent components are ext...
In this work we present a new technique of facial-image retrieval using constrained independent component analysis (cICA). We have employed cICA for the online extraction of those...
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...